Measuring Agent Success
Metrics, evaluation, and monitoring
TL;DR
Metrics, evaluation, and monitoring
> Overview
Traditional metrics (page views, click rates) do not capture agent quality. You need new metrics: task completion rate, hallucination rate, user satisfaction with agent output, cost per task, and latency percentiles. This module teaches PMs how to build an agent metrics dashboard, implement automated evaluation, and detect quality degradation.
> Why This Matters for Your Product
If you cannot measure it, you cannot improve it and you cannot justify investment to stakeholders. Agent quality is subjective and probabilistic: the same prompt might produce different results. You need automated evaluation pipelines that continuously score your agent's output, detect quality degradation, and alert when performance drops. This is how you build stakeholder confidence.
> Interactive & tools
Metrics dashboard (example)
Agent metrics dashboard (example)
Task completion rate
94% ↑
Quality score (LLM-as-Judge)
4.2/5 →
Hallucination rate
1.2% ↓
Cost per task
$0.012 ↓
Latency P95
8.2s →
Escalation rate
5% ↓
Core metrics: completion rate, quality score, hallucination rate, cost per task, latency P50/P95, CSAT, escalation rate, error rate.
Eval flywheel
The eval flywheel
Every production failure becomes a test case. Better evals → better agent → more trust → more usage → more edge cases → better evals.
Related Engineering Patterns
These are the technical patterns your engineering team will implement. Understanding them helps you have better conversations.
Key Product Decisions
- [01]What are your primary success metrics (completion rate, accuracy, CSAT)?
- [02]How do you define and detect hallucinations for your domain?
- [03]What is your cost budget per agent task?
- [04]How often should you evaluate agent quality (real-time vs. batch)?
Ask Your Engineering Team
- →What evaluation framework are we using?
- →Can we set up automated quality scoring with LLM-as-a-Judge?
- →What is our current hallucination rate and how do we track it?
- →Do we have alerting for quality degradation in production?
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